ON THE REDUCTION OF DESIGN LOAD CASES FOR FATIGUE ASSESSMENT OF MOORING LINES FOR OFFSHORE RENEWABLE ENERGY SYSTEMS

The design of offshore renewable energy systems requires evaluating numerous design load cases to comply with standards, with long-term fatigue assessment often being the most time-consuming aspect. Thousands of time-domain simulations are needed to capture the combined effects of environmental conditions, making the process computationally expensive and contributing to the already high Levelized Cost of Energy (LCOE) for offshore renewables.

To address this challenge, the study applies K-means clustering to reduce the number of environmental cases while maintaining accuracy in fatigue estimation. A sensitivity analysis confirms that 1000 clusters sufficiently capture key resource characteristics and accurately estimate fatigue damage. This approach significantly decreases the number of simulations required, reducing computational costs and improving the feasibility of large-scale offshore renewable energy design studies.